A novel synthesis of two decades of microsatellite studies on European beech reveals decreasing genetic diversity from glacial refugia.

Genetic diversity influences the evolutionary potential of forest trees under changing environmental conditions, thus indirectly the ecosystem services that forests provide. European beech (Fagus sylvatica L.) is a dominant European forest tree species that increasingly suffers from climate change-related die-back. Here, we conducted a systematic literature review of neutral genetic diversity in European beech and created a meta-data set of expected heterozygosity (He) from all past studies providing nuclear microsatellite data. We propose a novel approach, based on population genetic theory and a min-max scaling to make past studies comparable. Using a new microsatellite data set with unprecedented geographic coverage and various re-sampling schemes to mimic common sampling biases, we show the potential and limitations of the scaling approach. The scaled meta-dataset reveals the expected trend of decreasing genetic diversity from glacial refugia across the species range and also supports the hypothesis that different lineages met and admixed north of the European mountain ranges. As a result, we present a map of genetic diversity across the range of European beech which could help to identify seed source populations harboring greater diversity and guide sampling strategies for future genome-wide and functional investigations of genetic variation. Our approach illustrates how to combine information from several nuclear microsatellite data sets to describe patterns of genetic diversity extending beyond the geographic scale or mean number of loci used in each individual study, and thus is a proof-of-concept for synthesizing knowledge from existing studies also in other species. Supplementary Information: The online version contains supplementary material available at 10.1007/s11295-022-01577-4.

Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size.

Spatially explicit population genetic models have long been developed, yet have rarely been used to test hypotheses about the spatial distribution of genetic diversity or the genetic divergence between populations. Here, we use spatially explicit coalescence simulations to explore the properties of the island and the two-dimensional stepping stone models under a wide range of scenarios with spatio-temporal variation in deme size. We avoid the simulation of genetic data, using the fact that under the studied models, summary statistics of genetic diversity and divergence can be approximated from coalescence times. We perform the simulations using gridCoal, a flexible spatial wrapper for the software msprime (Kelleher et al., 2016, Theoretical Population Biology, 95, 13) developed herein. In gridCoal, deme sizes can change arbitrarily across space and time, as well as migration rates between individual demes. We identify different factors that can cause a deviation from theoretical expectations, such as the simulation time in comparison to the effective deme size and the spatio-temporal autocorrelation across the grid. Our results highlight that FST , a measure of the strength of population structure, principally depends on recent demography, which makes it robust to temporal variation in deme size. In contrast, the amount of genetic diversity is dependent on the distant past when Ne is large, therefore longer run times are needed to estimate Ne than FST . Finally, we illustrate the use of gridCoal on a real-world example, the range expansion of silver fir (Abies alba Mill.) since the last glacial maximum, using different degrees of spatio-temporal variation in deme size.

Recovery of silver fir (Abies alba Mill.) seedlings from ungulate browsing mirrors soil nitrogen availability.

Abies alba (Mill.) has a high potential for mitigating climate change in European mountain forests; yet, its natural regeneration is severely limited by ungulate browsing. Here, we simulated browsing in a common garden experiment to study growth and physiological traits, measured from bulk needles, using a randomized block design with two levels of browsing severity and seedlings originating from 19 populations across Switzerland. Genetic factors explained most variation in growth (on average, 51.5%) and physiological traits (10.2%) under control conditions, while heavy browsing considerably reduced the genetic effects on growth (to 30%), but doubled those on physiological traits related to carbon storage. While browsing reduced seedling height, it also lowered seedling water-use efficiency (decreased $\delta ^{13}$C) and increased their $\delta ^{15}$N. Different populations reacted differently to browsing stress, and for seedling height, starch concentration and $\delta ^{15}$N, population differences appeared to be the result of natural selection. First, we found that populations originating from the warmest regions recovered the fastest from browsing stress, and they did so by mobilizing starch from their needles, which suggests a genetic underpinning for a growth-storage trade-off across populations. Second, we found that seedlings originating from mountain populations growing on steep slopes had a higher $\delta ^{15}$N in the common garden than those originating from flat areas, indicating that they have been selected to grow on N-poor, potentially drained, soils. This finding was corroborated by the fact that nitrogen concentration in adult needles was lower on steep slopes than on flat ground, strongly indicating that steep slopes are the most N-poor environments. These results suggest that adaptation to climate and soil nitrogen availability, as well as ungulate browsing pressure, co-determine the regeneration and range limit of silver fir.

Fine-scale spatial genetic structure across the species range reflects recent colonization of high elevation habitats in silver fir (Abies alba Mill.).

Variation in genetic diversity across species ranges has long been recognized as highly informative for assessing populations' resilience and adaptive potential. The spatial distribution of genetic diversity within populations, referred to as fine-scale spatial genetic structure (FSGS), also carries information about recent demographic changes, yet it has rarely been connected to range scale processes. We studied eight silver fir (Abies alba Mill.) population pairs (sites), growing at high and low elevations, representative of the main genetic lineages of the species. A total of 1,368 adult trees and 540 seedlings were genotyped using 137 and 116 single nucleotide polymorphisms (SNPs), respectively. Sites revealed a clear east-west isolation-by-distance pattern consistent with the post-glacial colonization history of the species. Genetic differentiation among sites (FCT = 0.148) was an order of magnitude greater than between elevations within sites (FSC = 0.031), nevertheless high elevation populations consistently exhibited a stronger FSGS. Structural equation modelling revealed that elevation and, to a lesser extent, post-glacial colonization history, but not climatic and habitat variables, were the best predictors of FSGS across populations. These results suggest that high elevation habitats have been colonized more recently across the species range. Additionally, paternity analysis revealed a high reproductive skew among adults and a stronger FSGS in seedlings than in adults, suggesting that FSGS may conserve the signature of demographic changes for several generations. Our results emphasize that spatial patterns of genetic diversity within populations provide information about demographic history complementary to non-spatial statistics, and could be used for genetic diversity monitoring, especially in forest trees.

Correlational selection in the age of genomics.

Ecologists and evolutionary biologists are well aware that natural and sexual selection do not operate on traits in isolation, but instead act on combinations of traits. This long-recognized and pervasive phenomenon is known as multivariate selection, or-in the particular case where it favours correlations between interacting traits-correlational selection. Despite broad acknowledgement of correlational selection, the relevant theory has often been overlooked in genomic research. Here, we discuss theory and empirical findings from ecological, quantitative genetic and genomic research, linking key insights from different fields. Correlational selection can operate on both discrete trait combinations and quantitative characters, with profound implications for genomic architecture, linkage, pleiotropy, evolvability, modularity, phenotypic integration and phenotypic plasticity. We synthesize current knowledge and discuss promising research approaches that will enable us to understand how correlational selection shapes genomic architecture, thereby linking quantitative genetic approaches with emerging genomic methods. We suggest that research on correlational selection has great potential to integrate multiple fields in evolutionary biology, including developmental and functional biology, ecology, quantitative genetics, phenotypic polymorphisms, hybrid zones and speciation processes.

Adaptation to drought is coupled with slow growth, but independent from phenology in marginal silver fir (Abies alba Mill.) populations.

Drought is one of the most important selection pressures for forest trees in the context of climate change. Yet, the different evolutionary mechanisms, and their environmental drivers, by which certain populations become more drought tolerant than others is still little understood. We studied adaptation to drought in 16 silver fir (Abies alba Mill.) populations from the French Mediterranean Alps by combining observations on seedlings from a greenhouse experiment (N = 8,199) and on adult tress in situ (N = 315). In the greenhouse, we followed half-sib families for four growing seasons for growth and phenology traits, and tested their water stress response in a "drought until death" experiment. Adult trees in the field were assessed for δ 13C, a proxy for water use efficiency, and genotyped at 357 SNP loci. SNP data was used to generate a null expectation for seedling trait divergence between populations in order to detect the signature of selection, and 31 environmental variables were used to identify the selective environment. We found that seedlings originating from populations with low soil water capacity grew more slowly, attained a smaller stature, and resisted water stress for a longer period of time in the greenhouse. Additionally, adult trees of these populations exhibited a higher water use efficiency as evidenced by their δ 13C. These results suggest a correlated evolution of the growth-drought tolerance trait complex. Population divergence in bud break phenology was adaptive only in the second growing season, and evolved independently from the growth-drought tolerance trait complex. Adaptive divergence in bud break phenology was principally driven by the inter- and intra-annual variation in temperature at the geographic origin of the population. Our results illustrate the different evolutionary strategies used by populations to cope with drought stress at the range limits across a highly heterogeneous landscape, and can be used to inform assisted migration programs.

Adaptation to local climate in multi-trait space: evidence from silver fir (Abies alba Mill.) populations across a heterogeneous environment.

Heterogeneous environments, such as mountainous landscapes, create spatially varying selection pressure that potentially affects several traits simultaneously across different life stages, yet little is known about the general patterns and drivers of adaptation in such complex settings. We studied silver fir (Abies alba Mill.) populations across Switzerland and characterized its mountainous landscape using downscaled historical climate data. We sampled 387 trees from 19 populations and genotyped them at 374 single-nucleotide polymorphisms (SNPs) to estimate their demographic distances. Seedling morphology, growth and phenology traits were recorded in a common garden, and a proxy for water use efficiency was estimated for adult trees. We tested whether populations have more strongly diverged at quantitative traits than expected based on genetic drift alone in a multi-trait framework, and identified potential environmental drivers of selection. We found two main responses to selection: (i) populations from warmer and more thermally stable locations have evolved towards a taller stature, and (ii) the growth timing of populations evolved towards two extreme strategies, 'start early and grow slowly' or 'start late and grow fast', driven by precipitation seasonality. Populations following the 'start early and grow slowly' strategy had higher water use efficiency and came from inner Alpine valleys characterized by pronounced summer droughts. Our results suggest that contrasting adaptive life-history strategies exist in silver fir across different life stages (seedling to adult), and that some of the characterized populations may provide suitable seed sources for tree growth under future climatic conditions.

A Reference Genome Sequence for the European Silver Fir (Abies alba Mill.): A Community-Generated Genomic Resource.

Silver fir (Abies alba Mill.) is a keystone conifer of European montane forest ecosystems that has experienced large fluctuations in population size during during the Quaternary and, more recently, due to land-use change. To forecast the species' future distribution and survival, it is important to investigate the genetic basis of adaptation to environmental change, notably to extreme events. For this purpose, we here provide a first draft genome assembly and annotation of the silver fir genome, established through a community-based initiative. DNA obtained from haploid megagametophyte and diploid needle tissue was used to construct and sequence Illumina paired-end and mate-pair libraries, respectively, to high depth. The assembled A. alba genome sequence accounted for over 37 million scaffolds corresponding to 18.16 Gb, with a scaffold N50 of 14,051 bp. Despite the fragmented nature of the assembly, a total of 50,757 full-length genes were functionally annotated in the nuclear genome. The chloroplast genome was also assembled into a single scaffold (120,908 bp) that shows a high collinearity with both the A. koreana and A. sibirica complete chloroplast genomes. This first genome assembly of silver fir is an important genomic resource that is now publicly available in support of a new generation of research. By genome-enabling this important conifer, this resource will open the gate for new research and more precise genetic monitoring of European silver fir forests.

Detecting the genomic signal of polygenic adaptation and the role of epistasis in evolution.

Over the last decade, the genomic revolution has offered the possibility to generate tremendous amounts of data that contain valuable information on the genetic basis of phenotypic traits, such as those linked to human diseases or those that allow for species to adapt to a changing environment. Most ecologically relevant traits are controlled by a large number of genes with small individual effects on trait variation, but that are connected with one another through complex developmental, metabolic and biochemical networks. As a result, it has recently been suggested that most adaptation events in natural populations are reached via correlated changes at multiple genes at a time, for which the name polygenic adaptation has been coined. The current challenge is to develop methods to extract the relevant information from genomic data to detect the signature of polygenic evolutionary change. The symposium entitled "Detecting the Genomic Signal of Polygenic Adaptation and the Role of Epistasis in Evolution" held in 2017 at the University of Zürich aimed at reviewing our current state of knowledge. In this review, we use the talks of the invited speakers to summarize some of the most recent developments in this field.

What genomic data can reveal about eco-evolutionary dynamics.

Recognition that evolution operates on the same timescale as ecological processes has motivated growing interest in eco-evolutionary dynamics. Nonetheless, generating sufficient data to test predictions about eco-evolutionary dynamics has proved challenging, particularly in natural contexts. Here we argue that genomic data can be integrated into the study of eco-evolutionary dynamics in ways that deepen our understanding of the interplay between ecology and evolution. Specifically, we outline five major questions in the study of eco-evolutionary dynamics for which genomic data may provide answers. Although genomic data alone will not be sufficient to resolve these challenges, integrating genomic data can provide a more mechanistic understanding of the causes of phenotypic change, help elucidate the mechanisms driving eco-evolutionary dynamics, and lead to more accurate evolutionary predictions of eco-evolutionary dynamics in nature.

Genomic Quantitative Genetics to Study Evolution in the Wild.

Quantitative genetic theory provides a means of estimating the evolutionary potential of natural populations. However, this approach was previously only feasible in systems where the genetic relatedness between individuals could be inferred from pedigrees or experimental crosses. The genomic revolution opened up the possibility of obtaining the realized proportion of genome shared among individuals in natural populations of virtually any species, which could promise (more) accurate estimates of quantitative genetic parameters in virtually any species. Such a 'genomic' quantitative genetics approach relies on fewer assumptions, offers a greater methodological flexibility, and is thus expected to greatly enhance our understanding of evolution in natural populations, for example, in the context of adaptation to environmental change, eco-evolutionary dynamics, and biodiversity conservation.

Coupled effects of wind-storms and drought on tree mortality across 115 forest stands from the Western Alps and the Jura mountains.

Damage due to wind-storms and droughts is increasing in many temperate forests, yet little is known about the long-term roles of these key climatic factors in forest dynamics and in the carbon budget. The objective of this study was to estimate individual and coupled effects of droughts and wind-storms on adult tree mortality across a 31-year period in 115 managed, mixed coniferous forest stands from the Western Alps and the Jura mountains. For each stand, yearly mortality was inferred from management records, yearly drought from interpolated fields of monthly temperature, precipitation and soil water holding capacity, and wind-storms from interpolated fields of daily maximum wind speed. We performed a thorough model selection based on a leave-one-out cross-validation of the time series. We compared different critical wind speeds (CWSs) for damage, wind-storm, and stand variables and statistical models. We found that a model including stand characteristics, drought, and storm strength using a CWS of 25 ms-1 performed the best across most stands. Using this best model, we found that drought increased damage risk only in the most southerly forests, and its effect is generally maintained for up to 2 years. Storm strength increased damage risk in all forests in a relatively uniform way. In some stands, we found positive interaction between drought and storm strength most likely because drought weakens trees, and they became more prone to stem breakage under wind-loading. In other stands, we found negative interaction between drought and storm strength, where excessive rain likely leads to soil water saturation making trees more susceptible to overturning in a wind-storm. Our results stress that temporal data are essential to make valid inferences about ecological impacts of disturbance events, and that making inferences about disturbance agents separately can be of limited validity. Under projected future climatic conditions, the direction and strength of these ecological interactions could also change.

Evidence of divergent selection for drought and cold tolerance at landscape and local scales in Abies alba Mill. in the French Mediterranean Alps.

Understanding local adaptation in forest trees is currently a key research and societal priority. Geographically and ecologically marginal populations provide ideal case studies, because environmental stress along with reduced gene flow can facilitate the establishment of locally adapted populations. We sampled European silver fir (Abies alba Mill.) trees in the French Mediterranean Alps, along the margin of its distribution range, from pairs of high- and low-elevation plots on four different mountains situated along a 170-km east-west transect. The analysis of 267 SNP loci from 175 candidate genes suggested a neutral pattern of east-west isolation by distance among mountain sites. F(ST) outlier tests revealed 16 SNPs that showed patterns of divergent selection. Plot climate was characterized using both in situ measurements and gridded data that revealed marked differences between and within mountains with different trends depending on the season. Association between allelic frequencies and bioclimatic variables revealed eight genes that contained candidate SNPs, of which two were also detected using F(ST) outlier methods. All SNPs were associated with winter drought, and one of them showed strong evidence of selection with respect to elevation. Q(ST)-F(ST) tests for fitness-related traits measured in a common garden suggested adaptive divergence for the date of bud flush and for growth rate. Overall, our results suggest a complex adaptive picture for A. alba in the southern French Alps where, during the east-to-west Holocene recolonization, locally advantageous genetic variants established at both the landscape and local scales.

Detecting short spatial scale local adaptation and epistatic selection in climate-related candidate genes in European beech (Fagus sylvatica) populations.

Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. FST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an FST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.

Approximate Bayesian Computation (ABC) in practice.

Understanding the forces that influence natural variation within and among populations has been a major objective of evolutionary biologists for decades. Motivated by the growth in computational power and data complexity, modern approaches to this question make intensive use of simulation methods. Approximate Bayesian Computation (ABC) is one of these methods. Here we review the foundations of ABC, its recent algorithmic developments, and its applications in evolutionary biology and ecology. We argue that the use of ABC should incorporate all aspects of Bayesian data analysis: formulation, fitting, and improvement of a model. ABC can be a powerful tool to make inferences with complex models if these principles are carefully applied.

Performance of marker-based relatedness estimators in natural populations of outbred vertebrates.

Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent-offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i.e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.